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计数数据的贝叶斯半参数保序回归AI 解读

This article proposes a semiparametric Bayesian approach for inference on an unknown isotonic regression function, f(x), characterizing the relationship between a continuous predictor, X, and a count response variable, Y, adjusting for covariates, Z. A Dirichlet process mixture of Poisson distributions is used to avoid parametric assumptions on the conditional distribution of Y given X and Z. Then, to also avoid parametric assumptions on f(x), a novel prior formulation is…

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通过物种出现模型估计生物群落的规模与组成AI 解读

We develop a model that uses repeated observations of a biological community to estimate the number and composition of species in the community. Estimators of community-level attributes are constructed from model-based estimators of occurrence of individual species that incorporate imperfect detection of individuals. Data from the North American Breeding Bird Survey are analyzed to illustrate the variety of ecologically important quantities that are easily constructed and…

结果依赖抽样下连续结果回归模型的估计似然方法AI 解读

Many biomedical observational studies attempt to relate a continuous outcome to an environmental exposure and other important covariates. If the outcome is easier or cheaper to measure relative to the exposure of interest, then the outcome may be observed for every member of a finite-study population, whereas exposure measurements may be obtained only for a relatively small subsample of this population. Rather than selecting a simple random subsample of individuals for…

加速药物开发的二期与三期联合设计AI 解读

For late-stage clinical development, we propose combining phase 2 and 3 trials via a two-stage adaptive design. In the first stage, short-term safety and efficacy are examined, after which low doses that lack efficacy and high doses that cause safety concerns are eliminated from further evaluation. The trial continues to the second stage with doses that are not eliminated. For the second stage, the required sample size is adjusted to maintain power. All patients, including…

高维数据聚类中的贝叶斯变量选择AI 解读

Over the last decade, technological advances have generated an explosion of data with substantially smaller sample size relative to the number of covariates (p ≫ n). A common goal in the analysis of such data involves uncovering the group structure of the observations and identifying the discriminating variables. In this article we propose a methodology for addressing these problems simultaneously. Given a set of variables, we formulate the clustering problem in terms of a…

基于条件 Kendall τ 的失效时间与截断时间拟独立性检验AI 解读

Truncated survival data arise when the failure time is observed only if it falls within a subject-specific truncating set. Most analysis methods rely on the key assumption of quasi-independence, that is, factorization of the joint density of failure and truncation times into a product proportional to the individual densities in the observable region. Unlike independence of failure time and censoring time, quasi-independence can be tested. Tests of quasi-independence are…

二元反应生物测定中有效剂量的非参数估计札记AI 解读

For the common binary response model, we propose a direct method for the nonparametric estimation of the effective dose level. The estimator is obtained by the composition of a nonparametric estimate of the quantile response curve and a classical density estimate. The new method yields a simple and reliable monotone estimate of the effective dose-level curve α → EDα and is appealing to users of conventional smoothing methods as kernel estimators, local polynomials, series…

含随机效应的比例优势模型最大似然估计AI 解读

In this article we study the semiparametric proportional odds model with random effects for correlated, right-censored failure time data. We establish that the maximum likelihood estimators for the parameters of this model are consistent and asymptotically Gaussian. Furthermore, the limiting variances achieve the semiparametric efficiency bounds and can be consistently estimated. Simulation studies show that the asymptotic approximations are accurate for practical sample…

一般误差分布下 Lp 回归渐近性质概述AI 解读

We survey the asymptotic properties of regression Lp estimators under general classes of error distributions. It is found that the asymptotic distributions of Lp estimators depend crucially on p and the shape of the error distribution near the origin. A number of important features arise as a result, among which are (a) use of a small p may yield accelerated convergence rates for Lp estimators under certain classes of error distributions; (b) for p < 1, Lp regression should,…

用信息准则选择协整秩的蒙特卡洛研究AI 解读

We conduct Monte Carlo simulations to evaluate the use of information criteria (Akaike information criterion [AIC] and Schwarz information criterion [SC]) as an alternative to various probability-based tests for determining cointegrating rank in multivariate analysis. First, information criteria are used to determine cointegrating rank given the lag order in a levels vector autoregression. Second, information criteria are used to determine the lag order and cointegrating…

含 I(2) 变量的 VAR 协整参数约束检验札记AI 解读

We give a brief introduction to the vector autoregressive model for cointegrated I(2) variables and show how some plausible economic relations can be formulated in the I(2) framework in such a way that likelihood ratio tests for their validity are asymptotically χ2 distributed.The authors thank Paolo Paruolo for helpful comments and the ESF for financial support in the framework of the EMM network.

方差比检验：连续时间渐近框架下的尺寸与功效分析AI 解读

We consider the statistical properties of the variance ratio statistic in the context of testing for market efficiency defined by uncorrelated returns. The statistic is then the ratio of the variance of K-period returns to the variance of one-period returns scaled by K. We use a continuous-time asymptotic framework whereby we let the sample size increase to infinity keeping the span of the data fixed. We also let the aggregation parameter K increase such that K/T → κ as T,…

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GMM、GEL、序列相关与渐近偏差AI 解读

For stationary time series models with serial correlation, we consider generalized method of moments (GMM) estimators that use heteroskedasticity and autocorrelation consistent (HAC) positive definite weight matrices and generalized empirical likelihood (GEL) estimators based on smoothed moment conditions. Following the analysis of Newey and Smith (2004) for independent observations, we derive second order asymptotic biases of these estimators. The inspection of bias…

半参数平均导数的 Bootstrap 与 Edgeworth 修正AI 解读

In a number of semiparametric models, smoothing seems necessary in order to obtain estimates of the parametric component which are asymptotically normal and converge at parametric rate. However, smoothing can inflate the error in the normal approximation, so that refined approximations are of interest, especially in sample sizes that are not enormous. We show that a bootstrap distribution achieves a valid Edgeworth correction in the case of density-weighted averaged…

序列依赖非参数熵度量的渐近分布理论AI 解读

Entropy is a classical statistical concept with appealing properties. Establishing asymptotic distribution theory for smoothed nonparametric entropy measures of dependence has so far proved challenging. In this paper, we develop an asymptotic theory for a class of kernel-based smoothed nonparametric entropy measures of serial dependence in a time-series context. We use this theory to derive the limiting distribution of Granger and Lin's (1994) normalized entropy measure of…

终身等价尺度的半参数估计AI 解读

Abstract Pashardes ( 1991 ) and Banks et al. ( 1994 ) use parametric methods to estimate lifetime equivalence scales. Their approaches put parametric restrictions on the differences in within‐period expenditure needs across household types, the intertemporal allocation of expenditure, and the shapes of commodity demand equations. This paper puts parametric structure only on the differences in within‐period expenditure needs across household types. This implies structure on…

我没说，也不会说：SIPP中的动态回答误差AI 解读

Abstract Using state administrative records matched to the 1984 Survey of Income and Program Participation , we examine intertemporal relationships in response errors. False negative errors in reporting food stamps are highly correlated across interviews for the same household. Hypotheses that the error process can be explained by learning behaviour are not supported. Bivariate probit of response error in two periods reveals that responses to covariates are stable over time…

基于上升性质的蒙特卡洛 EM 算法AI 解读

Summary The expectation–maximization (EM) algorithm is a popular tool for maximizing likelihood functions in the presence of missing data. Unfortunately, EM often requires the evaluation of analytically intractable and high dimensional integrals. The Monte Carlo EM (MCEM) algorithm is the natural extension of EM that employs Monte Carlo methods to estimate the relevant integrals. Typically, a very large Monte Carlo sample size is required to estimate these integrals within…

序贯蒙特卡洛方法的停时重采样AI 解读

Summary Motivated by the statistical inference problem in population genetics, we present a new sequential importance sampling with resampling strategy. The idea of resampling is key to the recent surge of popularity of sequential Monte Carlo methods in the statistics and engin-eering communities, but existing resampling techniques do not work well for coalescent-based inference problems in population genetics. We develop a new method called ‘stopping-time resampling’, which…